Questions tagged [timeseries-segmentation]

Time series segmentation arises in time series analysis and digital signal processing. An input time-series is divided into a sequence of discrete segments in order to reveal the underlying properties of its source. Note that this is different from time series clustering!

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Clustering Data with Time and ~10 million records

I have a dataset with features like product categories, their dimensions, price, units sold on a given day. I want to create clusters out of this dataset (~12-15 million records) and I am using data ...
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2 votes
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1D cluster - Jenks optimization - Finding optimal number

I have a sample data variable shown below score 10, 11, 12, 90, 95, 97, 38, 37, 35 Instead of applying/binning data based on ...
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interpretation of aapc in R

I am running a joinpoint regression in R using the segmented package. I need to formulate annual average percent change values, and using aapc. The output that I receive gives me an estimate, ST.Er ...
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Dividing a data set into segments with consistent inner behavior, using segmentation algorithms and metrics for consistency

Context of the problem: I have signal data which was recorded in a software system and which shows the runtime of multiple processes over time. In total there are more than 900 processes each having ...
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Estimating duration of temporary exogenous predictor cox proportional hazard model

I have time-to-event survival data (ie., start, end, fate [death or censor] for each known individual). I am looking to model survival for a population of animals that are released onto a new ...
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2 votes
1 answer
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Robustly extracting subpatterns from time-series data

As part of an experiment, I need to collect time-series samples which are tightly associated with some input data. I send this data to an external device, and then collect the associated trace using ...
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Detecting household showing abnormal behavior

I am trying to figure out those household which have abnormal pattern in viewing one particular youtube channels. The data is of 12 weeks The households may fall into one of this category and many ...
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2 answers
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Choosing a changepoint detection algorithm

I've been reading up on changepoint algorithms (dynamic programming, Bayesian Online Changepoint detection, Hidden Markov Models, etc.) and am looking to implement an algorithm that has a certain set ...
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Which statistical techniques can be used to decide which definition of sets produces the most coherent grouping of data

To explain. I am a historian, and an almost complete statistical novice. I am interested in exploring the ways in which generational alignments might be identified, not via use of generational labels, ...
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Need help specifying my problem: time series segmentation with clustering?

I can't get any further with my segmentation/clustering/classification problem and need help in choosing the right tools, or rather in leading me to the right problem definition. I have a single long ...
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Acceptable level of mAP in computer vision applied to health applications

EDIT: This question is meant for those who previously understand what mAP means but for contextualizing this question properly, it is the mean average precision as defined by Microsoft COCO i.e. the ...
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Data balancing in image classification

I've to segment defects from an image. The image consists of only tomatoes with it's defects in it. The defects and tomatoes in the dataset are as follows: ...
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Meaning of sparse annotation for images?

what is sparse annotation? Is it pixel-wise labeling for images. what are the other types of annotation?
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what is the best approach in dealing with large dimension custom data for training and predicting deep learning models

i am trying to implement semantic segmentation for satellite images.My custom dataset has dimensions(height,width)in range (3000, 3000)what is the best approach for feeding(for training) and ...
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Deciding length of units in sound recognition for training HMMs

I am working on creating a method to detect changes from one song to another. Namely, I hope to use a Hidden Markov Model (HMM) in order to model a part of a song and check to see if it accurately ...
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2 answers
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Detection of music note sequence in audio signal

I have an audio signal which contains the combination of different western music notes(I know this combination in advance) and I want to identify the sequence of the music notes present in it. For ...
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How to use Matrix Profile for dimension reduction and clustering

Matrix Profile (MP) has been used for clustering time-series segments. In the slideshow tutorial featured on the MP website, they use a figure to demonstrate projecting segment similarity onto an M-...
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How to perform segmentation on multivariate time series?

Given a multivariate time series, which method could be applied to segment it into partitions of stationary signals. To give more context: I am given a set of acceleration signals in XYZ-Direction. ...
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Determine the n largest intervals of noise in an audio file

I have audio files that contain interviews with long periods of silence. n - Number of interviews for a given audio file. I need to split the audio into periods where the interviews are actually ...
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k means for segmenting time series [closed]

Now, I am trying to understand how to segment a multivariate time series using k- means. I understand that the basic concept is to use centroids of segments rather than centroids of data points and ...
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3 votes
3 answers
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segmentation of univariate irregular time series

this is my first post. I have an irregular time series that exhibits large shifts in both mean and in the direction of the trend. It looks something like this (though this is far cleaner than ...
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15 votes
3 answers
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How can I programmatically detect segments of a data series to fit with different curves?

Are there any documented algorithms to separate sections of a given dataset into different curves of best fit? For example, most humans looking at this chart of data would readily divide it into 3 ...
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5 votes
1 answer
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Clustering data into bins of variable sizes

I'd like to build a model (in R or excel) that takes in large amount of linear data and segments it into "bins". The linear data is an attribute that reflects what condition that section/record is at. ...
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Goodness of fit of linear model for Segmentation of GPS positions time series

I have some GPS coordinates series taken in regular time steps and I need to verify whether some chunks of the trajectories fit well as a straight line or not. The aim is to perform segmentation on ...
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9 votes
3 answers
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Differences between clustering and segmentation

I have read about piecewise aggregate approximation (PAA) mining time series data, sliding window, top down and bottom up approaches for time series segmentation but these are applicable to single ...
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6 votes
1 answer
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Hidden Markov Model segmentation of different proportions of binary data

I need to segment a sequence of 0s and 1s by their proportion at relatively large scales. As an example, let's define 5 different states that represent 5 different ratios of 1s & 0s. ...
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2 votes
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strucchange breakpoints command: does NA mean no breaks are identified?

I am using the package strucchange to analyze a monthly time series. I read it in as a zoo object. The series looks something like this: ...
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